Search Results - (( tree visualization learning algorithm ) OR ( evolution optimization bat algorithm ))

Multi-Swarm bat algorithm by Taha A.M., Chen S.-D., Mustapha A.

“…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”

Parse tree visualization for Malay sentence (BMTutor) by Muhamad Noor, Yusnita, Jamaludin, Zulikha

“…An algorithm in designing BMTutor is discussed in this paper.The algorithm of the software is done sequentially as followed: 1) tokenizing 2) checking the number of words, 3) searching and comparing process to check the spelling or conjunctions, 4) assigning each word with a certain word class, 5) matching with rules, and 6) delivering/producing output (sentence correction or parse tree visualization, word attribute components, and parse tree from sentence examples).Based on the testing conducted, output from the development process shows that the prototype can correct all 15 invalid sentences and can produce parse tree visualization for all 20 sentences.…”
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Visualisasi pohon sintaksis berasaskan model dan algoritma sintaks ayat bahasa Melayu by Yusnita, Muhamad Noor

“…Previous works that produce syntactic tree output has disregarded additional relevant components such as sentence checking, sentence correction, the syntax tree visualization and the words attributes of each sentence. …”
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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

“…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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The comparison of interactive 3D visualization between static and animated approaches for learning binary tree topic / Mohd Zulhisam Yaakub by Yaakub, Mohd Zulhisam

“…This shows that both 3D visualization methods implemented in this study can increase the student learning achievements and spatial abilities. …”
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Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

“…A maximum accuracy of 81% is obtained for Decision Tree algorithm during the prediction of crime. The findings demonstrate that employing Machine Learning techniques aids in the prediction of criminal events, which has aided in the enhancement of public security.…”
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Defect green coffee bean detection using image recognition and supervised learning by Shafian Izan Sofian

“…Therefore, in this research project, the process will be conducted by using an image classifier with the model of a machine learning algorithm which the candidates comprise of Support Vector Machine, k-Nearest Neighbour and Decision Tree. k-nearest neighbour has the highest F1-score (0.51) than the other two algorithms (Support Vector Machine: 0.50, and Decision Tree: 0.48). …”
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Color recognition wearable device using machine learning for visually impaired person by Bolad, Tarek Mohamed, Nik Hashim, Nik Nur Wahidah, Mohamad Hanif, Noor Hazrin Hany

“…The user can also hear the name of the color along with ‘feeling’ the vibration. Two algorithms were used to distinguish between colors; RGB to HSV color conversion in comparison with neural network and decision tree based machine learning algorithms. …”
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Decision tree as knowledge management tool in image classification by Kusrini, , Harjoko, Agus

“…Expert System has been grown so fast as a science that study how to make computer capable of solving problems that typically can only be solved by expert.It has been realized that the biggest challenge of developing expert system is the process include expert’s knowledge into the system.This research tries to model expert’s knowledge management using case based reasoning method.The knowledge itself is not inputted directly by the expert, but rather the system will learn the knowledge from what the expert did to the previous cases.This research takes image classification as the problem to be solved.As the knowledge development technique, we build decision tree by using C4.5 algorithm.Variables used for building the decision tree are the image visual features.…”
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Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins by Sidek L.M., Basri H., Marufuzzaman M., Deros A.M., Osman S., Hassan F.A.

“…Additionally, to predict the flood depth, a trained Decision Tree (DT)-based sorting algorithm is used in this method. …”

Car dealership web application by Yap, Jheng Khin

“…The transfer learning algorithm pre-trained the River adaptive random forest regressor and classifier by transferring the tree structures and weights from the Scikit-learn fitted random forest regressor and classifier, respectively. …”
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Wearable based-sensor fall detection system using machine learning algorithm by Ishak, Anis Nadia, Habaebi, Mohamed Hadi, Yusoff, Siti Hajar, Islam, Md. Rafiqul

“…When a fall event occurs, the real-time data is collected and placed in a *.CSV file. Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. …”
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Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

“…Integrating SSA and SVM machine learning algorithms improves decision-making processes, leading to better crop yield through early detection and timely nutrient management. …”
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Impact of data balancing and feature selection on machine learning based network intrusion detection by Barkah, Azhari Shouni, Selamat, Siti Rahayu, Zainal Abidin, Zaheera, Wahyudi, Rizki

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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization by Razali, Mohd Norhisham, Ibrahim, Norizuandi, Hanapi, Rozita, Mohd Zamri, Norfarahzila, Abdul Manaf, Syaifulnizam

“…Future research can explore more advanced machine learning algorithms, incorporate time-series analysis for temporal dependencies, and expand data collection from diverse organizational settings to improve the generalizability of predictive models.…”
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Enhancing understanding of programming concepts through physical games by Raja Yusof, Raja Jamilah, Habib, Ahsan

“…We produced in total 10 lesson games to illustrate variables, swapping, arrays, sorting algorithm particularly bubble sort, quicksort, selection sort, graph theory, dynamic programming, amortized analysis and trees. …”
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Analysis of hyperspectral reflectance for disease classification of soybean frogeye leaf spot using Knime analytics by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi

“…This analysis involved the implementation of machine learning (ML) algorithms, including decision trees, random forests, and stacking, to classify soybean FLS severity levels. …”
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Hybridization Of Optimized Support Vector Machine And Artificial Neural Network For The Diabetic Retinopathy Classification Problem by Kader, Nur Izzati Ab

“…Hence, this research aims to obtain optimal or near-optimal performance value in the study of diabetic classification using supervised machine learning. There are many algorithms available for classification purpose such as k-Nearest Neighbour, k-Means, Support Vector Machine, Decision Tree, Artificial Neural Network and Linear Discriminant Analysis. …”
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Exploring frogeye leaf spot disease severity in soybean through hyperspectral data analysis and machine learning with Orange Data Mining by Ang, Yuhao, Mohd Shafri, Helmi Zulhaidi, Al-Habshi, Mohammed Mustafa

“…Objectives: The main objective of the study is to classify the severity level of FLS disease in soybean using hyperspectral reflectance data and machine learning algorithms. Materials and Methods: We used hyperspectral reflectance data from healthy and FLS of soybeans. …”
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Content-based indexing of low resolution documents by Md Nor, Danial

“…We present hierarchy indexing techniques, whose foundation are tree and clustering. K-means clustering are used for visual features like colour since their spatial distribution give a good image’s global information. …”
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